Nevertheless, an FPGA option is too expensive for high-volume applications, such as domestic appliances; for those appliances, IR will produce configurable versions of the most common algorithms in ...

The AcceDSP synthesis tool enables System Generator for DSP to support both DSP system and algorithm modeling methods by generating System Generator IP blocks based on floating-point MATLAB models.

Yao says “The FPGA based DPU platform achieves an order of magnitude higher energy efficiency over GPU on image recognition and speech detection.” Deephi believes a joint optimization between ...

The NSF has funded projects that will investigate how deep learning algorithms run on FPGAs and across systems using the high-performance RDMA interconnect. Another project, led by Andrew Ng and ...

To dramatically simplify the path from image and signal processing algorithms to FPGA implementation, designers should choose an abstract language-based synthesis technology to use the executable ...

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). ZTE’s engineers used Intel’s midrange Arria 10 FPGA for a cloud inferencing ...

Microchip has released a C++ algorithm high-level synthesis design workflow for its PolarFire FPGAs. “A large majority of edge compute, computer vision and industrial control algorithms are developed ...

Using a design flow put together by Mentor Graphics and Altera, designers can implement complex DSP algorithms in high-performance FPGAs directly from ANSI C++ code. The flow, which is based on ...

In this special guest feature from Scientific Computing World, Robert Roe writes that FPGAs provide an early insight into possibile architectural specialization options for HPC and machine learning.

The PROC reconfigurable systems are used to accelerate complex algorithms that include DSP, image processing, national security and other performance critical domains.